Fair Class-Based Downlink Scheduling with Revenue Considerations in Next Generation Broadband Wireless Access Systems
Issue No. 06 - June (2009 vol. 8)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TMC.2009.30
Bader Al-Manthari , Queen's University, Kingston
Hossam Hassanein , Queen's University, Kingston
Najah Abu Ali , UAE University, Al-Ain
Nidal Nasser , University of Guelph, Guelph
The success of emerging Broadband Wireless Access Systems (BWASs) will depend, among other factors, on their ability to manage their shared wireless resources in the most efficient way. This is a complex task due to the heterogeneous nature, and hence, diverse Quality of Service (QoS) requirements of different applications that these systems support. Therefore, QoS provisioning is crucial for the success of such wireless access systems. In this paper, we propose a novel downlink packet scheduling scheme for QoS provisioning in BWASs. The proposed scheme employs practical economic models through the use of novel utility and opportunity cost functions to simultaneously satisfy the diverse QoS requirements of mobile users and maximize the revenues of network operators. Unlike existing schemes, the proposed scheme is general and can support multiple QoS classes with users having different QoS and traffic demands. To demonstrate its generality, we show how the utility function can be used to support three different types of traffic, namely best-effort traffic, traffic with minimum data rate requirements, and traffic with maximum packet delay requirements. Extensive performance analysis is carried out to show the effectiveness and strengths of the proposed packet scheduling scheme.
BWASs, packet scheduling, QoS, utility, opportunity cost, fairness.
Bader Al-Manthari, Hossam Hassanein, Najah Abu Ali, Nidal Nasser, "Fair Class-Based Downlink Scheduling with Revenue Considerations in Next Generation Broadband Wireless Access Systems", IEEE Transactions on Mobile Computing, vol. 8, no. , pp. 721-734, June 2009, doi:10.1109/TMC.2009.30